Visuomotor integration depends on a remarkable coherence among a number of interrelated subprocesses such as pattern recognition, pattern discrimination, decision to move, and guidance of movement. The brain is able to integrate these elementary cognitive processes by coordinating the activities of diverse neural structures in the face of continuously varying processing demands. The question of how this coordination operates is central to understanding the neural basis of visuomotor function. This proposal aims to develop new analytical tools to investigate the coordinated activity of distributed neuronal ensembles in the cerebral cortex of humans and non-human primates performing simple visuomotor tasks. It is motivated by recent theoretical developments (Bressler 1994, 1995, 1996, and 1997) predicting a general cortical mechanism allowing the flexible large-scale functional coordination of interacting neuronal ensembles. Hypotheses concerning this mechanism will be tested by analysis of field potential data recorded at NIMH from macaque monkeys performing a visuomotor pattern recognition task. The challenge is to develop and test new analytic approaches that characterize the multiple, complex interactions of large-scale distributed cortical networks. Earlier analysis of a small portion of this NIMH data set, reported in Nature in 1993, revealed shifting patterns of multi-site cortical synchronization during visuomotor processing, and implicated synchronization in the formation of functional relations within and between cortical areas. Standard pairwise techniques were employed to measure synchronization between field potential signals. Here, novel methods of time-series analysis are proposed that go beyond the simple detection of network interactions. Advances in signal processing technology will be utilized to also derive multi-site interaction patterns, to analyze the dependencies of functional relations on particular groups of neurons, and to measure the flow of information between cortical regions. This collaborative project will draw on the complementary strengths of Drs. Bressler and Ding. Dr. Bressler brings to the project over 15 years of experience in cognitive neuroscience, with expertise in the recording and analysis of neuroelectric data from humans to animals. He will provide theoretical oversight and the application of analytic tools to the field potential data set. Dr. Ding, although relatively new to cognitive neuroscience, has over 10 years of experience in linear and nonlinear dynamical systems analysis. He will provide the development of new analytical methods from a comprehensive dynamical systems perspective. This work is expected to (1) produce new insights into the dynamics of cortical information flow in visual perception and motor performance, (2) make available new digital signal processing tools for the investigation of large scale neural systems underlying other cognitive functions and, (3) provide a fresh perspective on the design of complex architectures for the execution of cognitive tasks by artificial neural network systems.